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Cover -- Book Title -- Copyright -- Table of Contents -- Acknowledgements -- Introduction -- Chapter One The Beginning 1842 - 1900 -- Chapter Two 1901 - 1914 -- Chapter Three The Great War -- Chapter Four 1917 - 1918 -- Chapter Five The Inter-War Years -- Chapter Six 1924 - 1926 -- Chapter Seven 1927 - 1930 -- Chapter Eight 1930 - 1933 -- Chapter Nine 1934 - 1936 -- Chapter Ten 1937 - 1939 -- Chapter Eleven The Second World War -- Chapter Twelve 1942 - 1944 -- Chapter Thirteen 1945 - 1950 -- Bibliography/Sources -- Back Cover.

Sydney Herbert Bywater Harris was an adventurer, a man possessed of great courage and charm, who fulfilled every schoolboy fantasy and really did 'live the dream'. The second youngest of seven children, the ordinary life held little appeal for Sydney so, in 1898, at the age of 17, he left home in Ilford for the Klondike gold rush. Arriving too late to make his fortune he decided to join the US Army. Two and a half years later, after seeing action in the Boxer Rebellion and the Philippines Insurrection, Sydney returned to England where he met and married Elsa de Verde Verder, a lady from an affluent Vermont family. A year later Sydney joined the Kings Colonials Imperial Yeomanry, later renamed the King Edward's Horse. Still seeking excitement, in August 1914 he transferred to the Royal Flying Corps and in 1916 went to France with 23 Squadron to fly the FE2b. Life expectancy for pilots on the front lines was very short and he was badly wounded while gun-spotting over enemy lines. After several months recovering he was posted to Turnberry as Chief Instructor and on the 13th August 1917, he was posted to Marske (by-the-Sea), with the rank of Lieutenant Colonel, to form and command No.2 Fighting School. In 1919 he was awarded the Air Force Cross. But war was not quite finished with Sydney. In 1936, fleeing imminent bankruptcy, he became involved with the International Brigades in the Spanish Civil War. Returning back to England he joined the RAFVR (Royal Air Force Volunteer Reserve) and when the Second World War broke out he was posted to Turnhouse as Section Controller. This really didn't suit him and, determined to see more action, at the age of 58, he arranged a transfer to France as Adjutant with No 1 Squadron where his duties included liaising with the French Air Force. He later transferred to 1 ATS near Perpignan and was one of the last to

In the works of Annie Ernaux, the alliance of desire and disobedience (which I borrow from Georges Didi-Huberman) crystallises a commitment driven by indignation and sustained, as it was in Camus's oeuvre, by a creative revolt against both the indignities endured by the dominated and the government's shameful acts towards them, as well as against the State's disengagement from public services and any instance of declinist discourse. Annie Ernaux's opposition to power transcends mere protest : reminiscent of Camus, who remains a great inspiration, a positive energy 'for' rather than merely 'against' drives her quest for truth, her belief in the exercise of freedom and her fight for dignity. Her engagement against all forms of injustice (whether it be French migration policy, the treatment of the Yellow Vests by the French authorities or the pension reform of 2023) confirms her role as a key protagonist of the re-politicization of the anti-capital movement. If Jean-Luc Mélenchon symbolises a form of counter-power, Ernaux, on the other hand, embodies the power of desire and boundless imagination. Politics and ethics come together in her stylistics (that encompasses accuracy of expression) and carry the hope of another, better life.

ABSTRACTObjectivesTo determine the relationship between known social complexity and model of primary care service deliveryApproachThe impacts of the social determinants of health are well described. To understand the contribution of specific factors on primary care service use we linked social data in the Population Health Research Data Repository at the Manitoba Centre for Health Policy to health system data. We included all patients visiting a Winnipeg clinic at least three times between 2010 and 2013. We allocated each participant to the primary care provider providing the majority of their care; and each provider was assigned to the model of care where they provided the majority of their clinical care. We developed eleven new indicators to describe social complexity such as: children in care, low income quintile, income assistance (welfare), high residential mobility, and involvement with the justice system. Results The cohort included 626,264 unique individuals of whom 53.1% were female. The majority of participants received their care from the fee for service (FFS) model (511,763) followed by 76,261 assigned to "reformed FFS". 16,536 and 12,178 were assigned to the 2 team-based care alternative funded models and 9,526 to the teaching clinic model. Patients with social complexities, except for newcomers, were more likely to attend the alternative funded clinics. The patients these clinics served were generally very complex with over 15% having more than 5 complexities compared to less than 5% of those attending the FFS models. Twice as many patients in the FFS models (60%) had no complexities compared to the alternative funded models.ConclusionThe availability of social data in population health repositories provides new opportunities to understand the distribution of these social factors amongst care providers and the impact of each on the health of populations. This new understanding can support focused interventions to address specific social risk factors and provide the evidence to support different models of primary care service delivery.

ABSTRACTObjectives To determine the relationships between five models of primary care service delivery and quality of care indicators in an urban population. Two fee-for-service (FFS) and three alternative-funded models of primary care service delivery were studiedApproach We allocated all Manitoba residents who had at least three visits to any primary care provider (PCP) at any Winnipeg clinic between 2010-2013 to the most responsible PCP (N = 626,264). We then allocated each PCP to a model of primary care service delivery. We created general linear mixed models to describe the relationship between each model of primary care and the dominant, traditional fee-for-service model for health services use, while controlling for a variety of PCP and patient factors, including patient social complexity.Results Patient social complexity was associated with poorer crude rates for many of the indicators. There were no differences among the models for hospital readmission within 30 days or specialist referral by the assigned PCP. Hospitalizations for ACSC were higher for one alternative funded model (1.98 OR, 1.38-2.83 95% CI), while non-indicated low back X-rays were lower for a different alternative funded model (0.14 OR, 0.03-0.59 95% CI). Ambulatory care visits to any PCP were lower for all three alternative funded models than the two FFS models. The family medicine academic teaching sites had lower rates of continuity of care (p< 0.5)Conclusion Overall, no model of primary care consistently outperformed the others. FFS models had higher rates of visits, but appeared to satisfy patient needs better because they had less use of telehealth services following visits. Teaching sites appeared to sacrifice continuity of care potentially to support other academic activities. Controlling for social complexity was associated with a reduction in the differences between models in indicator outcomes.

ObjectivePublicly funded healthcare delivery systems use projections to ensure the availability of adequate future service delivery. Planning cycles need to consider infrastructure, human resources, and other essential requirements with an adequate lead time. Projections are fraught with challenges due to multiple unknowns but new developments in modeling may be useful.
ApproachWe explored the available data to determine the best approach to modeling surgical demand. The Manitoba Population Research Data Repository includes 90+ databases linkable at the person level over time. These include the population registry which includes all Manitobans registered for the universal healthcare benefit. Hospital discharge abstracts include over 20 relevant diagnoses (ICD10) and procedure codes for each admission. Medical services claims include all physician services provides with ICD 9CM codes. Fee-for-service physicians are paid based on these and alternate funded physicians are required to submit shadow claims.
ResultsWe found 349,171 orthopedic procedures of which 18.1% were absent from the Medical claims files and 551,508 medical claims of which 27.5% lacked a corresponding hospital abstract. We also identified 230,717 ophthalmologic procedures in the hospital data of which 2.5% had no corresponding medical claim; of the 648,826 medical claims 66.2% had no matching hospital abstract. Resource requirements of procedures are reflected in the number and complexity of each procedure performed. Historical changes over time reflect changing demand (population growth and aging) balanced by available resources. Available resources cannot be predicted via modelling. The best fit based on the validation dataset was a Seasonal Autoregressive Integrated Moving Average model with a Mean Absolute Percentage Error (MAPE) of 5.327%. which translates to 94.7% accuracy.
ConclusionDespite the limitations of modeling based on past behavior, we were able to predict surgical demand with 95% accuracy. These projections are valid partly due to the persistence of historical constraints through the validation period. Policies that address these service provision limitations would precipitate a need to adjust the model.

IntroductionOn their 18th birthday children in custody of provincial Child and Family Services (CFS) age out, and are adults in control of their own care. An additional extended transitional services program was introduced several years ago to address gaps in the provicion of, and access to, adult social services during this change.
Objectives and ApproachUsing linked population based data from the Manitoba Population Research Data Repository, children in the custody of CFS who turned 18 during a 10 year study period were compared to children not in custody. For those in custody of CFS, we also compared individuals who participated in the extended transitional care services to those who opted out. Outcomes included use of health services and prescription drugs, social assistance, involvment with the justice system, living in social housing, and mental health outcomes. For most outcomes, the two year period prior to the 18th birthday and the two year period after were measured.
ResultsDuring the study period, 4656 children in care of CFS turned 18 while in custody. There were 2811 permanent wards, of which 1663 participated in the extended transitional services program. An additional 1845 non-permanent wards also turned 18 during the study period. Permanent wards were much more likely to be long term wards (greater than six years, ~65\%) compared non permanent wards (~17\%). Opioid prescription rates more than doubled in the two years after their 18th birthday and were about 6 times greater than prescription rates for those not in care of CFS. Criminal accusation rates did not change after their 18th birthday, were about equal for permanent and non-permanent wards. For the majority of outcomes, the transitional services program appeared to have little impact.
Conclusion/ImplicationsCompared to children not in care of CFS, rates of most outcomes were considerably higher for wards. Not all outcomes demonstrated a significant change over the transition period. By linking data from so many different government departments, extra attention can be focused on areas likely to have the greatest impact.

IntroductionFrailty is a state of vulnerability to diverse stressors emphasizing the importance of identifying the frail to support them. The burden of frailty in Canada is steadily growing. Today, approximately 25% of people over age 65 and 50% past age 85 – over one million Canadians – are medically frail.
Objectives and ApproachTo develop an administrative data definition of frailty to facilitate clinical and health system planning. We will validate the definition by linking the administrative data to electronic medical records (EMR) data. The EMR definition is based on a Machine Learning binarized frailty flag for patients with a Rockwood Clinical Frailty Score > 5 on physician chart audit. The sensitivity of the Machine Learning was disappointing: 28% (95% CI: 21% to 36%).specificity was: 94% (95% CI: 93% to 96%), positive predictive value: 53% (95% CI: 42% to 64%), negative predictive value: 86% (95% CI: 83% to 88%).
ResultsThere was little overlap between the EMR and administrative data definitions using the same population. Of the 29,382 eligible administrative data community dwelling patients over 65 years old, with a linkable EMR record, 2398 (8.15%) were identified as frail using the administrative data definition, but only 16.1% of these were frail according to the EMR definition. Of the 2396 who were identified as frail in EMR data, only 375 (15.7%) were identified as frail using the administrative data definition.
Conclusion/ImplicationsWe are not yet able to develop a reliable administrative data definition of frailty to identify community living individuals to support health service planning. The lack of agreement between the results obtained from EMR and administrative data definitions suggests that further refinement is necessary. Identification of frailty remains complex.

IntroductionA 2002 report described the gap in health status between First Nations (FN) and all other Manitobans (AOM). That report was widely quoted in the context of other initiatives recognizing the inequities in Canadian society.
Objectives and ApproachWe analyzed linked administrative data held in the Manitoba Population Research Data Repository to determine the health status and health care use of First Nations people. To provide context to the findings we compared First Nations to all other Manitobans, disaggregated by on-reserve off-reserve status, and presented our findings by Region and Tribal Council area. The 35 indicators were chosen to address First Nations priorities and providecomparisons with the previous study. Results were age and sex adjusted.
ResultsThe gap between FN and AOM has grown. Premature mortality rates are 3x higher for FN compared to AOM. Rates of death by suicides and suicide attempts are 5x higher for FN compared to AOM. Rates of opioid prescribing are 2.5x higher for single prescription, and 4.5x higher for multiple prescriptions for FN compared to AOM. Colorectal cancer screening rates are 2x higher among all other Manitobans compared to FN. Continuity of care is much lower in FN than in AOM. For FN, primary care is less likely to be provided close to home than for AOM
Conclusion / ImplicationsDespite initiatives like the Truth and Reconciliation Commission, and Indian Residential School survivors pursuing healing, the gap in health outcomes has increased. Underlying causes such as ongoing systemic racism and colonialism within health governance should be addressed.

BackgroundThe healthcare system in Manitoba, Canada has faced long wait times for many surgical procedures and investigations, including orthopedic and ophthalmology surgeries. Wait times for surgical procedures is considered a significant barrier to accessing healthcare in Canada and can have negative health outcomes for patients. We developed models to forecast anticipated surgical procedure demands up to 2027. This paper explores the opportunities and challenges of using administrative data to describe forecasts of surgical service delivery.
MethodsThis study used whole population linked administrative health data to predict future orthopedic and ophthalmology surgical procedure demands up to 2027. Procedure codes (CCI) from hospital discharge abstracts and medical claims data were used in the modelling. A Seasonal Autoregressive Integrated Moving Average model provided the best fit to the data from April 1, 2004 to March 31, 2020.
ResultsInitial analyses of only hospital-based procedures excluded a significant portion of provider workload, namely those services provided in clinics. We identified 500,732 orthopedic procedures completed between April 1, 2004 and March 31, 2020 (349,171 procedures identified from hospital discharge abstracts and 151,561 procedures from medical claims). Procedure volumes for these services are expected to rise 17.7% from 2020 (36,542) to 2027 (43,011), including the forecasted 43.9% increase in clinic-based procedures. Of the 660,127 ophthalmology procedures completed between April 1, 2004 and March 31, 2020, 230,717 procedures were identified from hospital discharge abstracts and 429,410 from medical claims. Models forecasted a 27.7% increase from 2020 (69,598) to 2027 (88,893) with most procedures being performed in clinics.
ConclusionResearchers should consider including multiple datasets to add information that may have been missing from the presumed data source in their research approach. Confirming the completeness of the data is critical in modelling accurate predictions. Forecast modelling techniques have evolved but still require validation.

IntroductionFrailty is a combination of factors that increase vulnerability to functional decline, dependence and/or death. Frailty cannot easily be defined by comorbidities or medical treatment alone. Accurate detection of frailty in practice and at a population level is needed. This may be achieved using a combination of data sources.
Objectives and ApproachWe construct algorithms that can identify frailty using electronic medical record (EMR) and administrative data. We linked EMR data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) nodes and the administrative (e.g. billings, hospitalizations) from Population Data BC and the Manitoba Health Policy Centre. Frailty was defined as individuals 65+ who were receiving home services, had specific chronic conditions, received specific diagnoses, and/or had specific lab or other clinical indicators. We describe sociodemographic characteristics, risk factors, prescribed medications, use and costs of healthcare for those identified as frail.
ResultsPeople were identified as frail in 2014 and all analysis was completed with 2015 data. Among those who were > 65 years, who had a record in both EMR and administrative data, 5\%-8\% (n=191 of 3,553, BC; n=2,396 of 29,382, MB) were identified as frail. There was a higher likelihood of being frail with increasing age and being a woman. In BC, those identified as frail have higher contacts with primary care (n=20 vs. n=10) and more days in hospital (n=7.4 vs. n=2.0) compared to those who are not frail. Twenty two percent of those identified as frail in 2014 died in 2015, compared to a mortality rate of 2\% among those who are not frail.
Conclusion/ImplicationsIdentifying and reporting on those who are frail in primary care as well as in communities could enable targeted communications with patients and families and community based resources in order to improve patient care, patients' and caregivers' quality of life and better use of the healthcare system.